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1661
Design and Research on a Reed Field Obstacle Detection and Safety Warning System Based on Improved YOLOv8n
Published 2025-05-01“…Compared to other algorithms, the proposed model maintains an optimal balance between parameter efficiency, computational cost, detection speed, and accuracy, exhibiting distinct advantages. …”
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1662
Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer
Published 2024-09-01“…Post-optimization results indicated a reduction in power loss costs from 4.11 × 10^5 to 1.05 × 10^5 units, representing a 25.54% decrease. …”
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1663
Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response
Published 2025-05-01“…When compared to leading optimization algorithms, the proposed approach showed better performance. …”
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1664
Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model
Published 2023-01-01“…Improvements in hyperspectral image technology, diversification methods, and cost reductions have increased the convenience of hyperspectral data acquisitions. …”
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1665
Machine Learning-Driven Optimization of Transport Layers in MAPbI₃ Perovskite Solar Cells for Enhanced Performance
Published 2024-01-01“…In this research work, among those eight ML models, the XGBoost algorithm shows high accuracy for predicting the power conversion efficiency (PCE) of the cell, achieving root mean square error (RMSE) of 0.052 and a coefficient of determination (R2) of 0.999. …”
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1666
Energy Storage Configuration Optimization of a Wind–Solar–Thermal Complementary Energy System, Considering Source-Load Uncertainty
Published 2025-07-01“…Firstly, a deterministic bi-level model is constructed: the upper level aims to minimize the comprehensive cost of the system to determine the energy storage capacity and power, and the lower level aims to minimize the system operation cost to solve the optimal scheduling scheme. …”
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1667
Improving agricultural management zoning involving Sentinel-2 timeseries, crop’s phenology stages and proximal soil sensing data
Published 2025-07-01“…Our hypothesis that the clustering based on soil and phenology separated vegetation data would improve the management zones was refuted. The vegetation cluster, which was based on the entire Sentinel-2 timeseries, exhibited optimal performance, for one field in Groß Kreutz, Germany. …”
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1668
Network Optimization of Fresh Products Cold Chain Considering Supply Disruption and Demand Fluctuation Under the Dual-Carbon Policy
Published 2025-05-01“…The research results provide valuable decision-making support for fresh cold chain enterprises to develop resilient and low-carbon network optimization strategies for cost reduction, efficiency improvement, and sustainable development.…”
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1669
Layout optimization of multi-level cold chain storage facilities in agricultural producing areas considering type and capacity constraints.
Published 2025-01-01“…Based on the above considerations, with the aim of minimizing the total daily cost, an optimization model for the layout of multi-level cold chain storage facilities is established to determine the number, location, type and capacity of cold chain storage facilities at the same time. …”
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1670
Meta-RHDC: Meta Reinforcement Learning Driven Hybrid Lyrebird Falcon Optimization for Dynamic Load Balancing in Cloud Computing
Published 2025-01-01“…By integrating reinforcement learning with advanced optimization techniques, Meta-RHDC significantly improves task scheduling and load balancing compared to existing methods such as Load Optimization Algorithm (LOA), Reinforcement Learning (RL), and Falcon Optimization Algorithm (FOA). …”
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1671
Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling
Published 2025-07-01“…High-frequency modal components undergo secondary decomposition using variational mode decomposition (VMD) to extract the optimal intrinsic mode function. Finally, an improved symbiotic biological search algorithm combined with a Bidirectional Gated Recurrent Unit (BiGRU) is used to accurately predict dam deformation.…”
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1672
Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer
Published 2024-11-01“…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
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1673
Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach
Published 2025-05-01“…With the widespread adoption of electric vehicles (EVs), optimizing their charging and discharging strategies to improve energy efficiency and extend battery life has become a focal point of current research. …”
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1674
Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate
Published 2025-01-01“…The application of GWO for hyperparameter tuning has resulted in a 37.3% reduction in root mean square error (RMSE), a 37.4% drop in mean absolute percentage error (MAPE), and a 2.06% improvement in <inline-formula> <tex-math notation="LaTeX">$\text {R}^{2}$ </tex-math></inline-formula> to improve the precision of prediction. …”
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1675
A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks
Published 2024-12-01“…Its master stage uses one out of three different algorithms—Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), or the Multi-Objective Ant Lion Optimizer (MOALO)—while the slave stage is always performed by a load flow analyzer. …”
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1676
Co-Optimization Operation of Distribution Network-Containing Shared Energy Storage Multi-Microgrids Based on Multi-Body Game
Published 2025-01-01“…Finally, based on the power interaction of microgrids to measure their contributions, an improved Shapley value cost allocation method is proposed, effectively achieving a balanced distribution of benefits among the distribution network, shared energy storage, and multi-microgrids, thereby improving overall operational revenue. …”
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1677
Enhanced Stability and Performance of Islanded DC Microgrid Systems Using Optimized Fractional Order Controller and Advanced Energy Management
Published 2025-04-01“…To address these issues, this study proposes the use of an optimized fractional order PI (FOPI) controller and an efficient energy management algorithm. …”
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1678
Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration
Published 2025-09-01“…This efficient strategy consists of the inherent complexities, which is solved by the NSGA-II algorithm. The multi-objective approach of optimization procedure performs Pareto solution sets that reflects trade-offs between remaining load variations and operational costs. …”
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1679
Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators
Published 2025-08-01“…Using Multi-Objective Particle Swarm Optimization (MOPSO), the strategy thereby incorporates three main objectives; minimizing grid load fluctuations, maximizing aggregator profits, and reducing user costs. …”
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1680
Joint Optimization of Berths and Quay Cranes Considering Carbon Emissions: A Case Study of a Container Terminal in China
Published 2025-01-01“…This study presents an integrated model that incorporates tidal factors into the joint optimization of berth and quay crane operations, addressing both service standards and emissions during port stays and crane activities, and further designs a PSO-GA hybrid algorithm, combining particle swarm optimization (PSO) with crossover and mutation operators from a genetic algorithm (GA), to enhance optimization accuracy and efficiency. …”
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